Enhanced flexible process optimizer

ABSTRACT

The invention describes a flexible process optimizer for recording and analyzing various parameters to improve the efficiency of a production process. The flexible process optimizer acquires and conditions signals from a variety of transducers mounted on a production machine. Through qualitative and quantitative data analysis, specific aspects of the production process which need improvement are identified. The qualitative evaluation looks at the presence, absence, level, rate of change or duration of certain features of the production cycle as revealed by the sensor data. The quantitative evaluation of data involves the computation of certain data attributes. By providing useful data acquisition and data analysis tools, necessary adjustments are made to the required parameters of the production process to provide improved efficiency. The results of the changes are immediately verifiable on the display of the flexible process optimizer.

This application claims priority as a continuation of pending U.S.patent application Ser. Nos. 11/345,410 filed Feb. 1, 2006, and11/744,915 filed May 7, 2007, which are continuations of U.S. patentapplication Ser. No. 10/764,615 filed Jan. 26, 2004, which issued asU.S. Pat. No. 7,246,023.

FIELD

This invention pertains to an apparatus for monitoring and controlling aproduction process. More specifically, this invention pertains to anapparatus connected to a production machine that acquires and analyzesdata about the production process and adjusts the production machine toimprove the efficiency of the production process.

BACKGROUND

Most industrial processes used for production of discrete components orfor continuous products involve a multitude of variables that affect thefinal product quality as well as the production efficiency orproductivity. An example of a continuous production system is a papermill producing rolls of paper of certain composition, thickness, andother characteristics to meet customer specifications. An example of adiscrete component production system is a precision grinding machinemaking automotive cam shafts, crankshafts, or other components.Maximizing the product quality as well as productivity in a competitiveenvironment requires a certain degree of control of the productionsystem. This is generally only possible with the help of real time dataof key process parameters and product quality attributes acquired usingsensors installed on the production equipment. Although productionequipment may possess the components needed to move the slides andspindles at numerically controlled rates or furnace controls to maintaina certain temperature, the sensors to provide the information about thesystem behavior are not always available and may have to be added. Theavailability of real time process data combined with the controllabilityof the production machines still requires the determination of a controlstrategy or methodology best suited for an effective process controlunder a given set of production conditions. To complicate mattersfurther, certain conditions such as incoming stock on each part or theinstantaneous sharpness of the tool may be dynamic variables andtherefore are generally not known.

Some attempts have been made in the past towards fully automatic controlof the process. However, this requires instrumenting the productionmachines to obtain real time information on the machine and spindlestiffness as well as the actual tool sharpness. Typical of the prior artare the devices of the following patents.

Patent Number Inventor Issue Date 4,855,925 Bhateja Aug. 8, 19894,570,389 Leitch, et al. Feb. 18, 1986 4,590,573 Hahn May 20, 19866,098,452 Enomoto Aug. 8, 2000 6,128,547 Tomoeda, et al. Oct. 3, 20006,234,869 Kobayashi, et al. May 22, 2001

Leitch, et al., describe an automatic adaptive system to maintain aconstant wheel sharpness without wheel breakdown. Hahn describes acomputer controlled technique for rounding up holes in a grinding takinginto account the spindle deflection. The inventions of Enomoto andTomoeda automatically control the final workpiece diameter using ameasuring head during grinding. Kobayashi describes measuring the groundworkpiece diameter using a gauge head to reveal any abrupt changes orlack of changes in part size during grinding.

The inventions identified above are generally directed to attempts atthe automatic control of a grinding operation based upon a specific,predetermined attribute of the workpiece. However, none of these priorart patents disclose how to optimize and control the grinding processbased upon broad criteria of workpiece quality attributes and systemproductivity, nor do they provide the flexibility to change theoptimization criteria according to the specific process or the desiresof the user. Finally, the prior art control systems require instrumentedmachines with sensors and gauge heads and, therefore, are generally notadaptable to existing grinding machines lacking the necessaryinstrumentation.

SUMMARY

An apparatus for recording various parameters of a production processand analyzing the information gained from the parameters to improve theefficiency of the production process is shown and described. Theflexible process optimizer combines data acquisition capabilities withdata analysis tools to provide a user with the ability to visualize howthe machine is behaving during the production process and what areasneed improvement. The flexible process optimizer acquires data fromsensors mounted on a production machine and plots the sensor data on adisplay allowing the user to see in detail what is really happeninginside the production process. The flexible process optimizer permitsthe user to control fully the measurement ranges, full scales, and otherfeatures of all the sensors used to monitor the process. From thequalitative sensor data display, the user can analyze the processsignatures in the time domain and the frequency domain to spotinefficiencies in the production process. By identifying theinefficiencies in the production process, the process parameters can beadjusted to reduce or eliminate the inefficiency thereby directlyimproving the efficiency of the production operation. In addition, theuser can compute specific quantitative parameters from the process data.Analyzing these specific values helps quantify the process capabilityfor comparison with other similar systems and to insure that the processdemands do not exceed the physical limitations of the production system.Having the qualitative data and the quantitative data provides a precisemeasure of the production system behavior and allows the performancelevels of different production operations to be compared.

BRIEF DESCRIPTION OF THE DRAWINGS

The above-mentioned features of the invention will become more clearlyunderstood from the following detailed description of the invention readtogether with the drawings in which:

FIG. 1 illustrates a flexible process optimizer of the present inventionin a production environment;

FIG. 2 is a block diagram of the flexible process optimizer;

FIG. 3 is a block diagram of the main circuit of the flexible processoptimizer;

FIG. 4 is a block diagram of a general purpose module circuit for usewith the flexible process optimizer;

FIG. 5 is a block diagram of a vibration module circuit for use with theflexible process optimizer;

FIG. 6 is a block diagram of a power module circuit for use with theflexible process optimizer;

FIG. 7 is a flow chart of the major functions of the flexible processoptimizer;

FIG. 8 is a flow chart of the initialization function of the flexibleprocess optimizer;

FIG. 9 is a flow chart of the data acquisition function of the flexibleprocess optimizer;

FIG. 10 is a flow chart of the data analysis function of the flexibleprocess optimizer;

FIG. 11 is a flow chart of the module detection function of the flexibleprocess optimizer of the present invention;

FIG. 12 is a flow chart of the hardware diagnostic function of theflexible process optimizer;

FIG. 13 is a flow chart of the calibration function for the dc inputs ofthe flexible process optimizer;

FIG. 14 is a flow chart of the calibration function for the differentialinputs of the flexible process optimizer;

FIG. 15 is a flow chart of the calibration function for the 4-20milliamp inputs of the flexible process optimizer; and

FIG. 16 illustrates a graph of infeed, part size, and power for onecycle of a production grinding process;

FIG. 17 illustrates a graph of the wheel hungriness parameter; and

FIG. 18 is a flow diagram of the calibration function for an linearvariable differential transformer input.

DETAILED DESCRIPTION

An apparatus for recording various parameters of a production processand analyzing the information gained from the parameters to improve theefficiency of the production process, or flexible process optimizer 100,is shown in the accompanying figures and described herein. The flexibleprocess optimizer 100 combines data acquisition capabilities with dataanalysis tools to provide a user with the ability to visualize how themachine is behaving during the production process and what areas can beimproved.

FIG. 1 illustrates the environment of the flexible process optimizer 100of the present invention. The flexible process optimizer 100 includestwo main components: an interface module 102 and a processing devicerunning the system and application software 104. In the illustratedembodiment, the flexible process optimizer 100 is shown with theinterface module 102 attached to a personal computer running the systemsoftware; however, those skilled in the art will recognize that theinterface module and the processing device can be integrated into asingle unit. The flexible process optimizer 100 acquires data fromsensors mounted on a production machine 106 and plots the sensor data ona display, thereby allowing the user to see in detail what is happeninginside the production process. The flexible process optimizer 100permits the user to control fully the ranges, full scales, and otherfeatures of all the sensors used to monitor the process. In theillustrated embodiment, the production machine 106 is a grinding machinewith a grinding wheel 108 adapted to engage and disengage a workpiece110. The grinding wheel 108 generally moves into and out of theworkpiece 110 along a line parallel to line 112. The workpiece 110 isgenerally moved along a line parallel to line 114 in relation to thegrinding wheel 108. From the qualitative sensor data display, the usercan analyze the process signatures to spot inefficiencies in theproduction process. By identifying the inefficiencies in the productionprocess, the process variables can be adjusted to reduce or eliminatethe inefficiency thereby directly improving the quality and productivityof the production operation. In addition, the user can compute specificquantitative values from the process data. Analyzing the specificparameter values helps quantify the process capability and the physicallimitations of the production system. Having the qualitative data andthe quantitative data provides a precise measure of the productionsystem behavior and allows the performance levels of differentproduction operations to be compared. Using this information, a balancedcontrol strategy can be developed and implemented.

FIG. 2 illustrates a block diagram of the flexible process optimizer 100of the present invention. The flexible process optimizer 100 accepts anumber of module circuits 202 that monitor various parameters throughtransducers or probes attached to a target machine 216. The outputs ofthe module circuits 202 are conditioned by an appropriate signalconditioning circuit 204. A processor interface 206 connects theflexible process optimizer 100 to an processing device 208, such as anexternal personal computer. In one embodiment, the processor interface206 includes an interface port known to those skilled in the art,including but not limited to PCMCIA, PCI, serial, parallel, IEEE 1394,and USB. Connected to the processing device are a display device 210 anda storage device 212. The display device 210 is used to display eitheror both of the raw data and the processed data. The display device 210also provides the user interface to permit the entry of user specificinformation for the production system, the desired sensor range, desireddisplay, the desired process control limits, and other setupinformation. The storage device 212 saves either or both of the raw dataand the processed data. Finally, the machine interface 214 communicatesdirectly with the controller of the target machine 216. Through themachine interface 214, the flexible process optimizer 100 reads thecurrent controller settings. The setting information is combined withthe values measured during the process cycle to allow the user to seehow the process responds to the controller settings. Through theflexible process optimizer 100, the user adjusts the controller settingsto optimize the process and the machine interface 214 adjusts thesettings of the controller in the target machine 216. Those skilled inthe art will recognize that the processing device can be integrated intothe flexible process optimizer without departing from the scope andspirit of the present invention.

FIG. 3 illustrates one embodiment of the main circuit 300 of theflexible process optimizer in greater detail. The main circuit 300includes a power supply 302. In one embodiment, the power supply 302 isa universal input (90 to 260 volts) switch mode power supply providing+3.3, +5, +12, −12, +15, and −15 volt dc outputs. The 3.3 and the 5-voltoutputs are generally used to power digital circuits while the 12 and 15volt outputs are generally used to power analog circuits. Those skilledin the art will recognize that other voltages can be supplied by thepower supply 302 as necessary. A digital interface circuit 304 on themain circuit 300 interfaces an analog-to-digital converter (ADC) card ofa personal computer and the flexible process optimizer 100. The specialcodes that are generated by the flexible process optimizer software aredecoded in this circuit. The internal buses are also generated by thedigital interface circuit 304. The main circuit 300 also includes anumber of module slots 306 in which various module circuits can beplugged to customize the flexible process optimizer 100. The set ofmodules plugged into the module slots 306 determines the configurationof the flexible process optimizer 100 and, in association with thesystem software, fixes the application of the flexible process optimizer100.

The main circuit 300 has several controls for adjusting variousparameters of the attached modules. A gain control circuit 308 generatesthe control signals required by the individual modules for applying again to the input signal. The gain control circuit 308 can include amultiple-stage gain control to allow both coarse and fine control of thegain or one or more single-stage gain controls accomplishing the sameeffect. An offset control circuit 310 generates the control signalsrequired by the individual modules for applying an offset to the inputsignal. The offset control circuit 310 can include a multiple-stageoffset control to allow both coarse and fine control of the offset orone or more single-stage offset controls accomplishing the same effect.The main circuit further includes a module latch control circuit 312that generates the control signals required for latching the mode,filter, LVDT excitation, coarse gain information in the individualmodules. It will be understood by those skilled in the art that thevarious controls can be replicated to provide the required number ofunique controls. Replication allows for individual control over separatemodules, for example gain and offset, or the generation of multipleunique signals for a single module, for example multiple latch controls.

A digital-to-analog converter (DAC) circuit 314 generates a diagnosticvoltage for the attached modules with the desired resolution. The DAC314 generates an appropriate diagnostic voltage, which can be adjustedwith the precision of the number of available millivolt steps undercontrol of the system software. The diagnostic voltage is also used forcalibrating the different sensors under control of the system software.A standard +5 or +10-volt reference 316 is included for calibrating themodule circuits and the various sensors under control of the systemsoftware. A light-emitting diode (LED) driver circuit 318 illuminates aplurality of LEDs that indicate the presence and/or status of thevarious modules present in the flexible process optimizer 100.

FIG. 4 illustrates one embodiment of a general purpose module circuit400 adapted to accept inputs from a sensor 406, such as a linearvariable differential transformer (LVDT), a 4 to 20 milliamp currentloop, a dc voltage sensor, or a differential voltage sensor for use inthe flexible process optimizer 100 of the present invention. The inputtype is selected from the system software. In order to directly acceptinputs from a variety of ac type LVDTs, a LVDT excitation anddemodulation circuit 402 is built in the module 400. The LVDT excitationand demodulation circuit 402 generates the necessary ac excitationvoltage and frequency for the LVDT primary. The excitation voltage andfrequency are varied under the control of the system software. The LVDTexcitation and demodulation circuit 402 also produces a dc voltagecorresponding to the LVDT displacement. Other inputs are accepted froman input conditioning circuit 404 that converts 4 to 20 milliamp anddifferential voltage signals to a dc voltage. The input conditioningcircuit 404 includes a preamplifier stage to avoid any loading on theoutput of sensors. Those skilled in the art will recognize that modulecan be modified to accept less than all of the inputs described withoutdeparting from the scope and spirit of the present invention. Forexample, the module can be configured without the LVDT excitationcircuit and corresponding input circuitry or, alternatively, the modulecan be configured without the input circuitry for accepting adifferential input or the input from a current loop.

The module 400 transfers signals to and from the flexible processoptimizer 200 through a module connector 426 adapted to be receivedwithin a module slot 300. A first latch 408 holds the value of the LVDTexcitation voltage and the types of input selected like DC, differentialetc. A second latch 410 holds the filter value. It holds one of thepossible values of the filter. Those skilled in the art will recognizeother devices such as a memory can be used for holding the filter orother values without departing from the scope and spirit of the presentinvention. A switching circuit 412 selects one of the inputs like dc,LVDT, +5V reference voltage, etc., under the control of the systemsoftware. The switching circuit 412 also contains an analog switch thatprovides a pass-through feature, which passes the input signal to theadjacent module hardware via the main circuit 300. This feature allowsany connected input to be calibrated to two different ranges through thehardware of two adjacent modules and the input data can be acquired,viewed, and saved on two separate channels. A hardware amplifier andfilter 414 is implemented using a low-pass analog or digital filtercircuit applied to the sensor output. There are a number of differenttime constants that can be selected under control of the systemsoftware. A DAC coarse offset control circuit 416 generates a coarseoffset voltage under control of the system software. In one embodiment,the maximum offset voltage is approximately 10 volts in steps of a fewmillivolts. A DAC fine offset control circuit 418 generates a fineoffset voltage under control of the system software. In one embodiment,the maximum offset voltage of a few millivolts in fractional millivoltsteps. A two-stage coarse gain amplifier 420 under control of the systemsoftware. In one embodiment, the two-stage coarse gain amplifier 420 isimplemented using a special low noise amplifier and offers precisiongain steps in the range of 1 to about 10,000. A third latch 422 holdsthe coarse gain value under control of the system software. A fine gainamplifier 424 amplifies the input with a gain in the range of aboutunity to about 10. The gain range of the fine gain amplifier 424 isdivided into a number of steps, for example offering up to 10,000 gainincrements between 0 and 10 and is selected through the system software.

FIG. 5 is a block diagram of a vibration module circuit 500 for use inthe flexible process optimizer 100 of the present invention. In oneembodiment, up to four piezoelectric vibration sensors 518 can beconnected to the vibration module circuit 500. No external power sourcefor the sensors 518 is required as power for the sensors is suppliedfrom the base current through the module circuit 500. The vibrationmodule circuit 500 transfers signals to and from the flexible processoptimizer 100 through a module connector 520 adapted to be receivedwithin a module slot 306. A piezoelectric vibration sensor 518 requiresa constant current power supply 502. A multiple-stage coarse gaincircuit 504, which in the illustrated embodiment is a two-stage circuit,is provided for each vibration sensor input. The system softwarecontrols the gain of each multiple-stage coarse gain circuit 504 insteps in the range of 1 to about 1,000. For the first and secondvibration sensor inputs, a first coarse latch circuit 506 holds the gainvalue of coarse gain amplifiers. A filter latch 508 holds the filterstep of the associated hardware amplifier and filter 510. Each hardwareamplifier and filter 510 is a low pass filter circuit with one of anumber different time constants that are controlled through the systemsoftware. The low pass filter is applied to the sensor signal afteramplifier through the multiple-stage course gain circuit 504. The thirdand fourth vibration sensor inputs are handled either simultaneously orindependently, as shown in FIG. 5. A second coarse latch 512 holds thegain value of the coarse gain amplifiers 504 associated with the thirdand fourth vibration sensors. There is no hardware filter associatedwith the third and fourth vibration sensor inputs in the illustratedembodiment; however those skilled in the art will recognize that any orall of the sensor inputs can include analog or digital filters withoutdeparting from the scope and spirit of the present invention.

A switching latch 514, under the control of the system software, holdsthe status of a switching circuit 516 such as the module and connectoridentifier, the diagnostic voltage, etc., thereby controlling the outputof the switching circuit 516. The switching circuit 516 switches to thesignal based on the value stored in the switching latch 514. Theswitching circuit 516 sends selected signal to the analog and digitaloutputs of the module.

FIG. 6 is a block diagram of a power module circuit 600 for use in theflexible process optimizer 100 of the present invention. The powermodule circuit 600 transfers signals to and from the flexible processoptimizer 100 through a module connector 618 adapted to be receivedwithin a module slot 306. A sensor range detection and range settingcircuit 602 interfaces with a power sensor 616, such as that produced byMonitech Systems, Inc., to read the range of the power sensor 616.Controlled by the system software, the sensor range detection and rangesetting circuit 602 provides the ability to change the range of thepower sensor 616. The power module circuit 600 also includes a sensorlatch 604, which is under the control of the system software, that holdsthe range value of the power sensor 616. A switching latch 606 holds thecommands from the system software to select the module identifier, thediagnostic voltage, the reference voltage, etc. A switching circuit 608switches to the signal based on the value stored in switching latch 606and sends the module identifier, the diagnostic voltage, or thereference voltage to the analog output of the power module circuit 600.A filter latch 610, which is controlled by the system software, holdsthe step value of hardware filter. A hardware filter and amplifier 612is a low pass filter circuit with one of a number of different timeconstants controlled through the system software. The low pass filter isapplied to the sensor signal after the amplifier output. A bufferamplifier 614 buffers the signal at the output stage.

Those skilled in the art will recognize that the number of valuesavailable, the number of stages available, the size of the steps, theranges of adjustment, and the maximum values can be varied based uponthe hardware components and the specifications of the various modulecircuits can vary without departing from the scope and spirit of thepresent invention.

The flexible process optimizer 100 allows the users of existing machineswithout built in sensors to obtain key data and observe patterns thatallow the user to gain control of the operation without making majoralterations to the machines in the production environment. The flexibleprocess optimizer 100 provides a balanced and easy-to-use controlstrategy and empowers the user to tailor the control to the user'sspecific need in any particular production operation. A balanced controlstrategy is defined in terms of controlling multiple output parametersof specific interest to a user.

One application of the flexible process optimizer 100 is monitoring andcontrolling a precision production grinding machine. A typicalproduction grinding operation consists of feeding the rotating grindingwheel into a rotating workpiece (or vice versa) by means of a slidecarrying the moving member. Material is removed from the workpiece at acertain rate during the interaction of the workpiece and the grindingwheel until the workpiece diameter reaches a desired size and surfacefinish. The infeed of the movable member, say the grinding wheel, iscontrolled carefully at various feed rates during the production cycleto provide the grinding pressures to remove the desired material as wellas to finish the work piece surface in an acceptable cycle time. Thefeed rates are dependent upon the capabilities of the machine and thegrinding wheel in use. In one embodiment, the flexible process optimizer100 takes the sensor signals, performs the needed signal conditioning,and displays the data on a visual display. The user analyzes the visualdisplay and makes manual control adjustments to the operation of theproduction grinding machine. In another embodiment, more sensors, dataanalysis features, and control lines are interfaced with the hardware ofthe production grinding system and its CNC control to allow control ofthe production process. The desired process control is effected bychanging the machine feed rates and the change points along with thewheel dressing conditions and wheel dressing frequency. During thisprocess the finished ground part quality data such as actual final size,taper, and, roundness are stored for quality inspection and reportingpurposes.

In production grinding, examples of the quantitative parameters mayinclude the grinding wheel hungriness; that is its ability to removematerial from a workpiece. Hungriness is usually not measured and yet itis a major cause of inefficiency and lack of control in productiongrinding operations. By nature, the key process parameters required foran effective process control depend upon the industrial process beingmonitored. In addition to the discrete component grinding and machiningindustry, continuous processes in industries such as: paper and pulpprocessing, food processing, pharmaceutical processing, and paints andchemical processing have a large number of special parameters such as:mixture consistency, temperatures, humidity, etc., which determine theproduct quality as well as the system productivity.

Using precision grinding to illustrate the present invention, there aretypically three sensors used for monitoring the machine. These include apower sensor to measure grinding wheel power consumption, an infeedsensor to measure the grinding wheel (or workpiece) slide, and a gaugehead sensor to measure the instantaneous diameter of the work pieceduring the actual grinding operation. The grinding wheel powerconsumption is considered a process output, the infeed is considered aprocess input, and the diameter is considered a product qualityattribute, which is indicative of the system output. With these threemeasurements recorded and displayed by the flexible process optimizer100, the user has sufficient information to determine the bestoptimization strategy and make the necessary adjustments to the grindingmachine to improve the efficiency of practically any grinding process.

For a balanced optimization and control of the process in a productiongrinding system, other parameters of interest include a ground componentend-to-end taper, the total grinding cycle time, and other features ofcertain process parameters during a particular phase of the grindingcycle. One such feature is the grinding power. Whether the grindingpower is kept high or low and is maintained at a certain level for acertain duration during the grinding operation affects the finalcomponent size (within the resolution capability of the in-process sizecontrol gauge) and the component surface roughness, roundness, andtaper. The need for a user definable flexible process optimizer arisesfrom the fact that the ground product quality on a given productionmachine varies with the condition of the grinding wheel and theequipment as well as incoming part quality and these also significantlyaffect the production cycle times.

In an advanced application of the flexible process optimizer to aprecision production grinding machine, multiple sensors are used. Thebasic sensors include pulse encoders or LVDT probes for monitoringmachine slide movements, speed sensors to track the grinding wheel andworkpiece rotational speed, power sensors for measuring the wattageconsumption of the wheel, the workpiece, or a rotary wheel dressingdevice, and a part size and geometry (taper or roundness) sensor.However, still more sensors may be used for monitoring the operation ofthe machine such as sensors to measure coolant flow rate, pressure, ortemperature, etc. The flexible process optimizer 100 of the presentinvention is adaptable, through replaceable module circuits, to measuremost any variable that causes or detects process variability. Inaddition to monitoring the process data, the flexible process optimizer100 can also measure the vibration at selected locations of the machineduring the actual grinding operation. Such information generally relateswith the condition of machine spindles and other structural pieces whichcan cause poor product quality deterioration and is taken at faster datarates than the typical slow process data designed to capture processchanges which are much slower.

FIG. 7 illustrates a flow chart of the major functions of the flexibleprocess optimizer 100, which are controlled through the processingdevice running the system software. The first major function is theinitialization of the flexible process optimizer 700, which includes theauto-detection of installed module circuits 702 and the automaticconfiguration and calibration of installed module circuits 704. Thesecond major function is the acquisition of data 710, which includesreading the sensors attached to a production machine 712 andconditioning the input signals 714. The third major function is theevaluation of the acquired data 720, which includes displaying theprocess data 722 and the evaluation of process efficiency based upon theconditioned process data 724. The last major function is the generationof control signals to adjust parameters of the production machine toimprove the efficiency of the production process 730, which includes thegeneration of control signals for adjusting the machine process 732 andthe reconfiguration of the production machine using the control signals734.

FIG. 8 charts the flow of the initialization function 700 in greaterdetail. First, the system software queries the flexible processoptimizer 100 to identify the installed module circuits 800. The systemsoftware automatically performs diagnostic testing 802 on the maincircuit and the installed module circuits to verify proper operation ofthe hardware. If the main circuit or any of the installed modulecircuits fail testing 804, the user is notified of the failure 806.Next, most of the properly functioning module circuits are automaticallycalibrated by the system software 808.

FIG. 9 charts the flow of the data acquisition function 710 in greaterdetail. The system software activates the various sensors 900. From theproduction machine, the various sensors collect signals 902 related tothe production process. The data acquisition process is monitored toidentify a problem in data acquisition, such as a malfunction in thecontroller, the monitor unit, or the module circuits, or thedisconnection of a sensor 904. If a data acquisition interruptionoccurs, the user is notified 906. The acquired data is conditioned foranalysis 908. Finally, the conditioned data is stored for analysis 910.Those skilled in the art will recognize that the analysis may occur inreal-time and rely solely on temporary storage or the data may be storedfor later analysis or historic purposes in a non-volatile storagemedium. Under control of the system software, the flexible processoptimizer 100 is capable of running unattended with scheduled datastorage intervals. The storage of data can also be triggered by theoccurrence of certain events as configured by the user.

FIG. 10 charts the flow of the data analysis function 720 in greaterdetail. The acquired and conditioned data is visually displayed forevaluation by a user 1000. From the visual display, the user canevaluate the production process and make adjustments to the productionprocess manually or verify that the production process is runningefficiently under control of the flexible process optimizer 100. Theuser is provided with control over the presentation of the data 1002.Some of the various parameters that are under the user's control includethe scale and the time base of the display window. An offset can beapplied to any data input to position the data input at a desiredlocation in the data display window. The polarity of any sensor inputcan be inverted by the system software for easier display and moremeaningful analysis. The system software also provides the ability tofilter electronic noise by applying a variable filter applied to a noisyinput or to noisy saved data. The system software also allows a user toview data from the same sensor at multiple scales and time basessimultaneously for improved evaluation of the process data. The systemsoftware also allows the user to connect a sensor to a single moduleslot 306 and view the same sensor data through two adjacent modules.Because the gain and offset of the modules are individually controlled,the same sensor data can be viewed with two different gains and/oroffsets. The on-screen position of the process data is variable by anautomatic offset removal function provided through the system software.Finally, the signal conditioning electronics of the flexible processoptimizer 100 are responsive to the system software to allow sensorcalibration for a wider range and actual operation at a smaller range.Using this technique data may seem off-scale while being acquired;however, saved data is repositionable when recalled. This enables theflexible process optimizer to capture data at high resolution in a muchwider effective range over a long period of time for unattended processmonitoring of production systems. Using data analysis tools,inefficiencies in the production process are identified 1004. Theprocess data is analyzed using various data analysis techniques known tothose skilled in the art, including statistical analysis, heuristic dataanalysis, pattern matching, and the application of specific algorithms.

FIG. 11 charts the flow of the module detection function 800 in greaterdetail. The module detection function 800 initializes the hardware bysetting the coarse gain and the fine gain to unity 1100 and by settingthe coarse offset and the fine offset to zero 1102. Next, the moduledetection function 800 disables the hardware filters to allow the rawinput to be read 1104. The module detection function 800 reads themodule identification voltage from the module 1106. The moduleidentification voltage is a voltage specific to a particular module.Identification of the module is completed by looking up the moduleidentification voltage read from the module in a look-up table 1108. Themodule detection function 800 is repeated until all attached modules areidentified. Those skilled in the art will recognize other structures andmethods for providing an identifier to the various module circuits andusing that identifier to determine which interchangeable module circuitsare attached to the flexible process optimizer 100.

FIG. 12 charts the flow of the hardware diagnostic function 802 ingreater detail. The hardware diagnostic function 802 initializes thehardware by setting the coarse gain and the fine gain to unity 1200 andby setting the coarse offset and the fine offset to zero 1202. Next, thehardware diagnostic function 802 disables the hardware filters to allowthe raw input to be read 1204. The hardware diagnostic function 802reads a reference voltage from the module 1206. The fixed referencevoltage is the base input voltage for the module. This reference voltagereading varies based upon the tolerances of the components making up themodule circuit. The reference voltage is compared to the ideal voltage,which would be read from an ideal module circuit. In general, thereference voltage is close to the ideal voltage so the hardwarediagnostic function 802 adjusts the fine gain until the referencevoltage equals the ideal voltage 1208. If the fine gain control can beadjusted so that the reference voltage equals the ideal voltage 1210,the hardware is considered to have passed the diagnostic check and thevalue of the fine gain is stored as the unity gain factor 1212.Otherwise, the user is notified of the hardware diagnostic failure 1214and other appropriate actions can be taken, such as terminating themonitoring process. The hardware diagnostic function 802 is repeated toverify the proper operation of each attached module.

FIG. 13 charts the flow of the dc input calibration function 1300, whichis a sub-function of the calibration function 808 in greater detail. Thedc input calibration function 1300 initializes the hardware by settingthe coarse gain and the fine gain to unity 1302 and by setting thecoarse offset and the fine offset to zero 1304. The dc input calibrationfunction 1300 reads a reference voltage from the module 1306. Thereference voltage is compared to a known voltage range, which representsthe input range of the dc input 1308. If the reference voltage is withinthe known voltage range 1310, the hardware is considered to be properlycalibrated. Otherwise, the user is notified of the hardware calibrationfailure 1312 and other appropriate actions can be taken, such asterminating the monitoring process. The dc input calibration function1300 is repeated to verify the calibration of each attached module usingdc inputs.

FIG. 14 charts the flow of the differential input calibration function1400, which is a sub-function of the calibration function 808 in greaterdetail. The differential input calibration function 1400 reads theminimum sensor voltage from the configuration file 1402. The maincircuit generates the minimum sensor voltage 1404 and the differentialinput calibration function 1400 adjusts the coarse offset and the fineoffset to null the minimum sensor voltage 1406. With the minimum sensorvoltage 1406 nulled, the differential input calibration function 1400calculates the differential voltage 1408 and the differential voltage isgenerated by the main circuit 1410. The module circuit gain is thenadjusted until the differential voltage is equal to a known referencevoltage 1412. If the gain control can be adjusted so that thedifferential voltage equals the reference voltage 1414, the hardware isconsidered to be properly calibrated. Otherwise, the user is notified ofthe hardware calibration failure 1416 and other appropriate actions canbe taken, such as terminating the monitoring process. The differentialinput calibration function 1400 is repeated to verify the properoperation of each attached module using differential inputs.

FIG. 15 charts the flow of the 4-20 milliamp current input calibrationfunction 1500, which is a sub-function of the calibration function 808in greater detail. The 4-20 milliamp current input calibration function1500 reads an input current and converts the input current into avoltage 1502 and an offset equivalent to the minimum sensor voltage isapplied to null it 1504. Next, the 4-20 milliamp current inputcalibration function 1500 calculates the difference 1506 between theoffset and the voltage and a differential voltage is generated by themain circuit 1508. The module circuit gain is then adjusted until thedifferential voltage is equal to a known reference voltage 1510. If thegain control can be adjusted so that the differential voltage equals thereference voltage 1512, the hardware is considered to be properlycalibrated. Otherwise, the user is notified of the hardware calibrationfailure 1514 and other appropriate actions can be taken, such asterminating the monitoring process. The 4-20 milliamp current inputcalibration function 1500 is repeated to verify the proper operation ofeach attached module using 4-20 milliamp current inputs.

Of all the inputs, the LVDT input is the most difficult to configure.The system software of the flexible process optimizer 100 greatlysimplifies the LVDT configuration and calibration. FIG. 18 charts theflow of the LVDT input calibration function. First, the calibrationroutine is initialized. This involves user entry scale informationincluding the maximum scale, which is the maximum value of the LVDTtravel in units of length, and the calibrated full scale, which is themaximum value of the LVDT travel in units of voltage 1800. The flexibleprocess optimizer 100 then sets the gain to unity and the offset to zero1802. A prompt from the flexible process optimizer 100 requires the userto move the LVDT through the entire range of travel of the plunger 1804.The system software records the minimum voltage and the maximum voltageproduced by the LVDT and quickly analyzes the voltage data to identifythe linear region of the LVDT 1806. Another prompt from the flexibleprocess optimizer 100 requires the user to position the resting point ofthe LDVT within the linear region 1808. With the LDVT operating withinthe linear region, the offset and the gain are optimized for the LDVTinput 1810. This involves adjusting the offset so the value of the LDVToutput appears to be zero at the resting point. The gain is adjusted sothat the LDVT output is a known reference value when the LDVT is movedto the maximum travel extent. If the gain control can be adjusted sothat the LDVT output voltage equals the reference voltage 1812 at themaximum travel extent, the LDVT hardware is considered to be properlycalibrated. Otherwise, the user is notified of the hardware calibrationfailure 1814 and other appropriate actions can be taken, such asterminating the monitoring process.

The flexible process optimizer 100 provides the user the ability toobserve the results of a particular production process setup. From theoutput of the flexible process optimizer 100, the user can determine thechanges necessary to improve the efficiency of the production process.The user then makes the changes to certain specific machine, gage andsystem control settings through the controller of the productionmachine. The flexible process optimizer 100 allows the user toimmediately verify that the changes produced the desired result. Thebest process improvement strategy is determined by the user based uponthe process sensor data and the product quality data available throughthe flexible process optimizer 100, which the user selects based uponcriteria of importance to the user for the specific production processbeing monitored. Referring again to the example of a grinding system,such conditions may include the sharpness of a grinding wheel, incomingstock amount variations on the component, and any weaknesses in themachine components due to wear. These conditions are not easilyaccounted for in conventional control systems; however, through theflexible process optimizer 100 of the present invention, the user isprovided the ability to both see and deal with these and otherconditions.

One example of process improvement or optimization in a productiongrinding system for precision component manufacturing is discussed insome detail. However, those skilled in the art will recognize that theflexible process optimizer 100 allows a similar approach to be appliedto any discrete component manufacturing or continuous process industryoperation. Referring to the grinding process cycle data of FIG. 16 showsthe wheel-workpiece infeed 1600 having four feed rates FR1, FR2, FR3,FR4 for a grinding wheel feeding into a part being ground. The changepoints B, C, D, E, F, G represent the times within the production cycleat which the feed rate is adjusted. The total infeed travel distance isthe difference between the grinding wheel position when contact is firstmade with the workpiece B and the grinding wheel position at thebeginning of the spark-out period F. To one skilled in the art, theproduction cycle can be visualized by looking at the infeed curve 1600.The movement between change points A and B represents the rapid approachfeed rate, before actual grinding takes place. The first feed rate FR1(change points B to C) represents the rough (fast) grinding feed rate.The second feed rate FR2 (change points C to D) represents the mediumgrinding feed rate. The third feed rate FR3 (change points D to E)represents the fine grinding feed rate. The fourth feed rate FR4 (changepoints E to F) represents the finish grinding feed rate. There is nofurther infeed during the spark-out period between change points F andG. Retraction of the grinding wheel occurs between change points G andH.

On the time axis, the time between start of the infeed A and the end ofthe wheel retraction H represents the total duration of the activegrinding cycle when the wheel and workpiece are programmed to engagewith each other. The total duration does not include other components ofa complete production cycle such as part unload and load, any indexingof wheel or workpiece required to position them correctly for grinding,wheel dressing in production or other similar operation when the wheelis not actually in contact with the part, or waiting for the completionof other operations. Setting the machine and controlling the operationtypically involves setting the feed rates FR₁, FR₂, FR₃, FR4 and all thechange points B, C, D, E, F, G from the rapid advance of wheel to itsretraction after grinding has taken place. FIG. 16 also shows the powerconsumption of the grinding wheel spindle 1602, which is obtained from apower sensor, and the instantaneous size of the workpiece 1604 duringthese various grinding feed rates, which is obtained from an in-processgage head positioned on the workpiece during the grinding cycle.

The flexible process optimizer 100 displays a continuous stream ofgrinding cycles as successive components are ground in productionallowing the user to see not only the features of any single grindingcycle but also spot any cycle-to-cycle variations in the importantfeatures such as feed rates or change points, the power levels atdifferent feed rates, and the pattern of the size generation curve fromthe in-process gage data. The flexible process optimizer 100 thus givesthe user the ability to monitor multiple production process parametersand to make changes to optimize the cycle pattern and the consistency ofthe cycle pattern from workpiece to workpiece.

The system software offers many functions and features which allow auser the flexibility needed to analyze and optimize a productionprocess. These features generally relate to the configurability andusability of the flexible process optimizer 100, which allows the userto focus on analyzing the process, and to the capabilities that enhancethe performance and value of the flexible process optimizer 100 to theuser. Such features include the ability to compute values for certainparameters during live data acquisition or reviewing previously saveddata, providing the user with useful information not generally availablewhen attempting to improve a process.

One feature is an user selectable pause during data acquisition. Theinclusion of a pause during data acquisition conserves memory, reducesdata file sizes, and provides the user with flexibility during theacquisition operation. The occurrence and duration of a data acquisitionpause is visible to the user on any data screen window during both livedata acquisition and recall. Multiple data acquisition pauses arepossible on any data screen.

The data display screens used to visually analyze the production processare designed to present a panoramic view of the data. When used with along time base, the extended viewing area allows the user to view datafor both the current and previous process cycles for ready comparison.

The data screens grant the user virtually unlimited control of thevisual display. The user is free to change the input data scales, hidedata for any input, change the color of the data plot lines in the datawindow, apply offsets of user selected amounts to position any inputdata anywhere on the data screen, invert any input data, and applyfilters to eliminate unwanted frequencies or harmonics in the data beingviewed.

The system software allows the user to obtain the instantaneous value ofcertain useful parameters at any point during the data acquisitionprocess. Some of the available instantaneous values include the slope ofthe data, the average value of the data, the “area” under the curve overa certain time period, and the maximum or minimum values of the data,and the relative value of the data in relation to an user-definedreference. All instantaneous values are tabulated with time and can besaved, if desired. In addition, the system software can automaticallycompute the instantaneous values at user selected intervals.

The system software offers the user the ability to create an overlayfrom data obtained during the current data acquisition or frompreviously saved data. The data used to create the overlay can beunadjusted, expanded, or compressed as desired by the user. A savedoverlay can be used as a background during data acquisition orsuperimposed on recalled data for comparison and qualitative analysispurpose. The visual presentation of the overlay is adjustable giving theuser the flexibility to change the data plot colors, apply offsets toreposition the data and change the full scale range of the data in theoverlay.

Recognizing the importance of documentation in any monitored process,the system software has the ability to capture any screen of data duringdata acquisition and data recall. In each case, the user can adjust thevisual presentation of data, capture the screen image, and store thescreen image in common graphical file formats such as JPEG or TIFF.

During process monitoring, large amounts of data are commonly acquired.However, not all of the data is useful in evaluating the processefficiency. The system software offers the user the flexibility to saveonly the portion of the data acquired that is of interest instead offorcing the storage of all acquired data. Each data screen is identifiedby a unique screen number and the user can enter the range of screennumbers to be saved. Alternatively, the user can bring up cursors on anyacquired data screens to identify the specific data to be saved.

The system software includes the capability to track gradual shifts(i.e., drift) in data resulting from slowly changing conditions such astool wear and thermal expansion or contraction of machine members overtime. Similarly, the system software is capable of detecting abruptchanges in the scale and/or the offset of the data, which is useful foridentifying instantaneous events such as intentional size compensationsteps or random machine slide mispositioning because of stick-slip. Theaccumulated total of such offsets due to gradual or abrupt discrete stepchanges over an user-defined period is readily available to the user forreview.

The user's ability to extract derivative data files is another functionof the system software. The user has the ability to recall any targetprocess previously saved data file, and identify a section of the dataof real interest, and save that as a new derivative data file retainingthe full functionality of any saved data file.

The system software also allows the user to select certain sensor inputsof special interest and view them in a separate window with anuser-defined visual presentation, e.g., the user can choose the plotcolors, the offsets, and the scales for the selected inputs. The usermay also select to show or hide any input in the separate window.

Through the system software, the flexible process optimizer 100 can beconfigured to enable or disable inputs as desired from the availablemodule circuits. The visual presentation of input data is customizableallowing the user to enter data identification labels and otherpertinent information, including the user's notes and comments, for thevarious inputs. The user can enter the desired full-scale range for anysensor input within the sensor's capability. The customization andconfiguration information is saved in the data file and can be edited asnecessary.

The flexible process optimizer 100 has the ability to monitor vibrationdata simultaneously as it monitors process data. Vibration data isrelatively fast compared to the main process data. The vibration datatypically occurs at frequencies around a few kilohertz and is usuallycollected over a short time period often no more than a fraction of asecond. By way of comparison, the process cycle in a typical discretecomponent production lasts several seconds or even minutes and,therefore, requires relatively slower data acquisition speeds. Thesystem software recognizes the fact that the need to capture vibrationin machine spindles, slides, and other components may change or may beof special interest during certain phases of a process cycle.Accordingly, the system software allows the user to capture vibrationdata either on demand or continuously along with the slow process data.The two data types are saved in separate data files or combined in asingle data file at the user's discretion. The information about whenthe vibration data was acquired in a process cycle is also saved in thedata file.

As previously discussed, the system software allows the flexible processoptimizer 100 to be customized for most specific applications byfacilitating the plotting of computed process parameters specific to aparticular production process. The ability to plot multiple parametersis often needed for a thorough engineering analysis of the process andthe production system capabilities and limitations and enables the userto readily visualize the effects of machine setup and process changes,which is vital for process improvement or optimization of any existingoperation.

In the example of a production grinding system, the computed processparameters include cycle time analysis, cycle-to-cycle consistency, andwheel hungriness. The cycle time analysis function performs a detailedbreakdown of the times used on the individual components of a completeprocess cycle. A process cycle typically consists of various stages andcomponents, which relate with the events taking place during thesestages. Example may include a slide moving in rapidly to approach a partready to be ground at the grinding cycle or the final disengagement ofthe grinding wheel from the ground work piece at the end of the cycle.Through the cycle time analysis function, the operator can evaluate theoverall production efficiency and determine the percentage of the totalcycle time spent in each stage of the cycle. By comparing the cycle timeanalysis data from one operation with other similar operations, the userhas the ability to evaluate and troubleshoot the production system. Inaddition, the user has a useful tool to evaluate the consistency ofcycle times from piece to piece.

In addition to the consistency in the various cycle times, the systemsoftware provides a tool to check for variations in the behavior of theproduction system through the cycle-to-cycle consistency function. Thebehavioral variations include variations in stock on incoming parts,misfeeding of feed slides on the machine, improper settings on a sizecontrol gage, and changes in the ability of the wheel to remove materialfrom a part. Such variations appear as distinct features or changes inthe shapes of the data curves for different sensors during a processcycle. The cycle-to-cycle consistency analysis performs a quantitativeanalysis of a number of key parameters that are relevant to a particularprocess cycle. With respect to the example of the grinding system, therelevant parameters include: the spark-out time, the total cycle time,the spark-out power, the maximum grinding power, the total area underthe curve, the apparent (total) stock removal, and the slopes of theinfeed curves.

The flexibility inherent in the flexible process optimizer 100 alsoallows the system software to compute and save special parameters thatdetermine, and may limit, the system performance, that continuouslychange over time, and that may not be easy to control in real time.Returning to the example of the production grinding process, one suchspecial parameter is the grinding wheel hungriness, which represents theability of the grinding wheel to remove material from a workpiece.Grinding wheel hungriness continually changes based upon the length ofservice of the grinding wheel since installation of the wheel ordressing of the grinding and the relative hardnesses of the grindingwheel and the workpiece being ground.

The grinding wheel hungriness function derives present hungriness valueof the grinding wheel from power consumption data obtained from a powersensor input and the feed rate data or the slide position slope data.FIG. 17 illustrates a typical graph of grinding wheel hungrinesscharting the material removal rate per unit width versus power per unitwidth for the cycle data of FIG. 16. Points P₂, P₃, and P₄ represent thesteady state power values during the feed rates FR₂, FR₃, and FR4 inFIG. 16 and P₀ is the idle power at the beginning and the end of thecycle. The plot is typically linear and the slope of this line, whichrepresents the volumetric material removal rate per kilowatt of grindingpower, is referred to as the grinding wheel hungriness (H). As the wheelengages in grinding each workpiece, it gradually dulls and the loss ofsharpness is reflected in the computed hungriness parameter. Trackingthe hungriness of the grinding wheel provides a user a quantitativecriteria for determining key cycle setup parameters including how andwhen a wheel needs resharpening through dressing.

It should be emphasized that, although a production precision grindingsystem is used for illustrating this invention, the flexible processoptimizer 100 is applicable to a vast majority of manufacturingoperations in numerous industries. In addition to discrete componentmanufacturing like production grinding, other industries benefiting fromthe flexible process optimizer 100 of the present invention includepaper and pulp manufacturing, food and pharmaceuticals processing,petrochemical processing, and many others. The user's ability to adaptthe process optimization strategy based on visual display and somequantitative analysis of real time process sensor data that reflects thesystem behavior under the production conditions in use, permitsoptimization for both productivity and product quality in a balancedmanner with instant feed back to confirm that the desired control isactually being achieved. The actual changes made to optimize the processcan be made easily on the machine's CNC system settings or other manualadjustments normally possible on the machine.

From the foregoing description, it will be recognized by those skilledin the art that various embodiments of the invention provide devices andmethods for monitoring a production machine that allow data display andanalysis to develop and execute an immediate flexible processoptimization methodology that is verifiable on the display of theflexible process optimizer. The flexible process optimizer allows theuser to change the process control strategy based on the observed actualbehavior of the production system as revealed by sensors mounted on themachine for this purpose.

While the present invention has been illustrated by description ofseveral embodiments and while the illustrative embodiments have beendescribed in detail, it is not the intention of the applicant torestrict or in any way limit the scope of the appended claims to suchdetail. Additional advantages and modifications will readily appear tothose skilled in the art. The invention in its broader aspects istherefore not limited to the specific details, representative apparatusand methods, and illustrative examples shown and described. Accordingly,departures may be made from such details without departing from thespirit or scope of applicant's general inventive concept.

1. A method for measuring electrical signal parameters that areindicative of one or more characteristics of a manufacturing process,and analyzing waveforms derived from the measured electrical signalparameters to optimize the manufacturing process, the method comprisingthe steps of: (a) acquiring first data related to a first electricalsignal parameter indicative of a measure of nominal material removalfrom a component of manufacture at a given time in a production cycle;(b) acquiring second data related to a second electrical signalparameter indicative of a measure of power consumed by a materialremoval tool at any time during the production cycle; (c) generatingfirst and second waveforms corresponding to the first and second data;and (d) observing the first and second waveforms on a display device asadjustments are made to optimize the manufacturing process.
 2. Themethod of claim 1 wherein step (a) comprises acquiring first dataindicative of a position of the material removal tool relative to anyportion of the component of manufacture as material is removed from thecomponent of manufacture during the period of time.
 3. The method ofclaim 1 wherein: step (a) comprises acquiring the first data indicativeof a measure of material removed from the component of manufactureduring a grinding operation; and step (b) comprises acquiring the seconddata indicative of a measure of power consumed by a grinding wheelduring the grinding operation.
 4. The method of claim 1 furthercomprising adjusting a rate of removal of material from the component ofmanufacture to optimize the manufacturing process, the adjusting basedat least in part on the analysis of the first and second waveforms. 5.The method of claim 1 wherein the first electrical signal parameter is aprimary input variable which is controllable by an operator during themanufacturing process, and the second electrical signal parameterindicates a response of the material removal tool to changes in theprimary input variable.
 6. An apparatus for measuring electrical signalparameters that are indicative of one or more characteristics of amanufacturing process performed by a production machine, and analyzingwaveforms derived from the measured electrical signal parameters, theapparatus comprising: a first sensor module for measuring a firstelectrical signal indicative of a primary variable in the manufacturingprocess during a period of time, where the primary variable representsan aspect of the manufacturing process that is controllable by anoperator of the production machine; a second sensor module for measuringa second electrical signal indicative of a secondary variable in themanufacturing process during the period of time, where the secondaryvariable represents a response of the production machine to a change inthe primary variable; a processing device in communication with thefirst and second sensor modules for generating first and secondwaveforms corresponding to the first and second electrical signals; anda display device in communication with the processing device, thedisplay device for displaying the first and second waveforms to provideinformation useful in making adjustments to optimize the manufacturingprocess.
 7. The apparatus of claim 6 wherein the primary variablecorresponds to an amount of material removed from a component ofmanufacture during the period of time, and the secondary variablecorresponds to power consumed by a material removal tool during theperiod of time.
 8. The apparatus of claim 7 wherein the first electricalsignal is indicative of a position of the material removal tool relativeto any portion of the component of manufacture as material is removedfrom the component of manufacture during the period of time.
 9. Theapparatus of claim 7 wherein the first electrical signal is indicativeof a measure of material removed from the component of manufactureduring a grinding operation, and the second electrical signal isindicative of power consumed by a grinding wheel during the grindingoperation.
 10. The apparatus of claim 6 further comprising a machineinterface in communication with the processing device and incommunication with a controller of the production machine, the machineinterface for receiving information from the processing device foradjusting settings of the controller to optimize the manufacturingprocess.
 11. An apparatus for measuring electrical signal parametersthat are indicative of one or more characteristics of a manufacturingprocess performed by a production machine, and analyzing waveformsderived from the measured electrical signal parameters, the apparatuscomprising: a sensor module for generating a first electrical signalindicative of a parameter of the manufacturing process at a first time;a processing device in communication with the sensor module, theprocessing device for receiving and processing the first electricalsignal to generate a first waveform based thereon; a data storage devicefor storing the first waveform; the sensor module for generating asecond electrical signal indicative of the parameter of themanufacturing process at one or more second times occurring after thefirst time; the processing device for receiving and processing thesecond electrical signal to generate a second waveform based thereon; adisplay device in communication with the processing device, the displaydevice for generating a graphic overlay of the first and secondwaveforms to allow simultaneous viewing of the first and secondwaveforms; and an input device in communication with the processingdevice, the input device for accepting commands from a user to controlthe processing device to selectively modify the graphic overlay of thefirst and second waveforms on the display device.
 12. The apparatus ofclaim 11 wherein the processing device receives and processes the firstand second electrical signals over an extended time that includes thefirst time period during which a first repetition of a repetitive stepof the manufacturing process is performed and the one or more secondtime periods during which one or more second repetitions of therepetitive step are performed after the first time period, whereby thegraphic overlay of the first and second waveforms provides forsimultaneous viewing of information related to the first and one or moresecond repetitions of the repetitive step.
 13. The apparatus of claim 11wherein the processing device generates the first waveform at a firstamplitude scale and the second waveform at a second amplitude scale thatmay be the same as or different from the first amplitude scale, and theinput device accepts commands from the user to adjust one or more of thefirst amplitude scale of the first waveform and the second amplitudescale of the second waveform displayed on the display device.
 14. Theapparatus of claim 11 wherein the display device generates the graphicoverlay comprising the first waveform displayed having a first displaycharacteristic and the second waveform displayed having a second displaycharacteristic that may be different from the first displaycharacteristic, wherein the first and second display characteristics areselected from the group consisting of a first color, a second color, afirst line type and a second line type.
 15. The apparatus of claim 11wherein the input device accepts commands from the user to control theprocessing device to modify the graphic overlay on the display device byshifting the first waveform with respect to the second waveform or byshifting the second waveform with respect to the first waveform.
 16. Theapparatus of claim 11 wherein the input device accepts commands from theuser to control the processing device to modify the graphic overlay byadjusting an amplitude or time scale of one or more of the first andsecond waveforms on the display device.
 17. The apparatus of claim 11wherein the second waveform is based on a real-time second electricalsignal.
 18. The apparatus of claim 11 further comprising a machineinterface in communication with the processing device and incommunication with a controller of the production machine, the machineinterface for receiving information from the processing device to adjustsettings of the controller to optimize the manufacturing process. 19.The apparatus of claim 11 wherein the input device is further foraccepting commands from the user for entry of information to bedisplayed as identification labels or comment fields on the displaydevice in association with the first or second waveforms.
 20. A methodfor measuring electrical signal parameters that are indicative of one ormore characteristics of a manufacturing process, and analyzing waveformsderived from the measured electrical signal parameters to optimize themanufacturing process, the method comprising the steps of: (a)calibrating at least one sensor module over a first amplitude range; (b)acquiring sensor data related to an electrical signal parameter usingthe at least one sensor module over the first amplitude range; and (c)generating a real-time waveform corresponding to the sensor data on adisplay device over a second amplitude range that is less than orgreater than the first amplitude range, wherein the second amplituderange is adjustable in real time, and wherein the real-time waveform isgenerated in a time scale that is adjustable in real time as sensor datais acquired.
 21. The method of claim 20 further comprising: step (c)including generating on the display device a graphic overlay of multiplewaveforms corresponding to two or more of: the sensor data in the firstamplitude range in real time, the sensor data in the first amplituderange stored in a memory device, the sensor data in the second amplituderange in real time, and the sensor data in the second amplitude rangestored in the memory device; and (d) accepting commands from a user toselect the sensor data to be included in the graphic overlay on thedisplay device.
 22. A method for measuring electrical signal parametersthat are indicative of one or more characteristics of a manufacturingprocess, and analyzing waveforms derived from the measured electricalsignal parameters to optimize the manufacturing process, the methodcomprising the steps of: (a) acquiring sensor data related to one ormore electrical signal parameters using at least one sensor module; (b)generating a first waveform corresponding to the sensor data on adisplay device in a first window, wherein the first waveform has a firsttime scale and a first amplitude scale, wherein the first amplitude andtime scales are adjustable in real time; and (c) generating a secondwaveform corresponding to the sensor data on the display device in thefirst window or in a second window that may be positioned on the displaydevice independently of the first window, wherein the second waveformhas a second time scale that is different from the first time scale, anda second amplitude scale that is different from the first amplitudescale.
 23. A method for measuring electrical signal parameters that areindicative of one or more characteristics of a manufacturing processperformed by a production machine, and analyzing waveforms derived fromthe measured electrical signal parameters to optimize the manufacturingprocess, the method comprising the steps of: (a) providing one or moresensors attached to the production machine for generating one or moreelectrical signals indicative of operational characteristics of theproduction machine; (b) processing the one or more electrical signals togenerate operational characteristic data, (c) selecting time andamplitude settings for a display device to display one or more waveformscorresponding to the operational characteristic data, (d) displaying theone or more waveforms on the display device, (e) observing the one ormore waveforms on the display device to monitor the manufacturingprocess, (f) capturing a graphic image of the one or more waveformsdisplayed on the display device; and (g) storing the graphic image in astorage device for future display.
 24. A method for measuring electricalsignal parameters that are indicative of one or more characteristics ofa manufacturing process performed by a production machine, and analyzingwaveforms derived from the measured electrical signal parameters tooptimize the manufacturing process, the method comprising the steps of:(a) attaching a plurality of sensors to the production machine forgenerating sensor signals indicative of operational characteristics ofthe production machine, the plurality of sensors selected from the groupconsisting of vibration sensors, position sensors, form sensors, powersensors, fluid characteristic sensors, temperature sensors and pressuresensors; (b) processing the sensor signals to generate sensor data, (c)selecting time and amplitude settings for a display device to displaythe sensor data, (d) displaying two or more waveforms corresponding tothe sensor data from two or more of the plurality of sensor signalssimultaneously on the display device, and (e) observing the two or morewaveforms on the display device to monitor progress of the productionprocess.
 25. The method of claim 24 wherein step (d) further comprisesselecting any combination of the two or more waveforms to besimultaneously displayed on the display device, wherein the selection ofwaveforms for display is controlled by processing commands executed by aprocessor of a process monitoring device.